Exploring daily wind data using the Meteostat Python Library

Group Members: Travis, Ira, Micah

Course: Data Science – Phase 1
Goal: Explore and compare wind trends in distinct U.S. regions


Source: Meteostat Python API

Dataset Type: Aggregated weather observations per station

Key Variables
  • wspd: Average wind speed (km/h)
  • wdir: Mean wind direction (degrees)
  • tavg: Average air temperature (°C)
  • coco: Condition code

Time Period: 2024

Locations: ~30

Frame: Hourly, Daily, Monthly with a focus on Hourly

Units: Metric (km/h, degrees, °C)


#Start of Data ::: {.panel-tabset}

Regional Wind Analysis by Speed and Direction
Hourly Averages 2024 | Data: Meteostat
latitude longitude Wind Statistics
Speed (km/h) Direction (°)
Case Studies
Key West, FL 24.5551 -81.78 68.3 91.0
Honolulu, HI 21.3069 -157.8583 64.1 54.0
Oklahoma City, OK 35.4676 -97.5164 63.3 142.0
Anchorage, AK 61.2181 -149.9003 29.2 358.0
Midwest
Cleveland, OH 41.4993 -81.6944 64.5 227.0
Chicago, IL 41.8781 -87.6298 57.0 259.0
Detroit, MI 42.3314 -83.0458 55.9 248.0
Des Moines, IA 41.5868 -93.625 55.5 246.0
Milwaukee, WI 43.0389 -87.9065 54.5 297.0
Minneapolis, MN 44.9778 -93.265 45.4 307.0
Kansas City, MO 39.0997 -94.5786 44.0 2.0
Northeast
Buffalo, NY 42.8864 -78.8784 74.1 243.0
Boston, MA 42.3601 -71.0589 61.5 278.0
Philadelphia, PA 39.9526 -75.1652 49.9 297.0
Albany, NY 42.6526 -73.7562 43.3 263.0
Portland, ME 43.6591 -70.2568 41.2 313.0
Pittsburgh, PA 40.4406 -79.9959 40.7 299.0
New York, NY 40.7128 -74.006 38.3 300.0
Southeast
New Orleans, LA 29.9511 -90.0715 69.6 133.0
Jacksonville, FL 30.3322 -81.6557 52.3 81.0
Miami, FL 25.7617 -80.1918 47.3 81.0
Tampa, FL 27.9506 -82.4572 41.8 49.0
Charlotte, NC 35.2271 -80.8431 36.5 319.0
Raleigh, NC 35.7796 -78.6382 34.0 345.0
Atlanta, GA 33.749 -84.388 28.6 357.0
West
Denver, CO 39.7392 -104.9903 48.6 180.0
San Francisco, CA 37.7749 -122.4194 48.2 294.0
Salt Lake City, UT 40.7608 -111.891 47.0 154.0
Las Vegas, NV 36.1699 -115.1398 45.2 319.0
Los Angeles, CA 34.0522 -118.2437 39.6 208.0
Portland, OR 45.5152 -122.6784 39.2 333.0
Phoenix, AZ 33.4484 -112.074 37.7 128.0
Seattle, WA 47.6062 -122.3321 30.0 191.0
Legend: 🔵North 🔴East 🟡South 🟢West | Darker = Stronger

city_name Albany, NY Anchorage, AK Atlanta, GA Boston, MA Buffalo, NY Charlotte, NC Chicago, IL Cleveland, OH Denver, CO Des Moines, IA ... Philadelphia, PA Phoenix, AZ Pittsburgh, PA Portland, ME Portland, OR Raleigh, NC Salt Lake City, UT San Francisco, CA Seattle, WA Tampa, FL
region
Case Studies NaN 29.2 NaN NaN NaN NaN NaN NaN NaN NaN ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
Midwest NaN NaN NaN NaN NaN NaN 57.0 64.5 NaN 55.5 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
Northeast 43.3 NaN NaN 61.5 74.1 NaN NaN NaN NaN NaN ... 49.9 NaN 40.7 41.2 NaN NaN NaN NaN NaN NaN
Southeast NaN NaN 28.6 NaN NaN 36.5 NaN NaN NaN NaN ... NaN NaN NaN NaN NaN 34.0 NaN NaN NaN 41.8
West NaN NaN NaN NaN NaN NaN NaN NaN 48.6 NaN ... NaN 37.7 NaN NaN 39.2 NaN 47.0 48.2 30.0 NaN

5 rows × 33 columns




  1. How do wind patterns change by region?

  2. What are some case studies of extreme weather?

  3. How do geographical features (lakes, oceans, mountains, deserts, plains) impact wind patterns?